Currently, many applications based on DBs are present, and a DBMS that performs a series of processing and managements relating to DBs has become very important. One of the features of the DBMS is to deal with a large amount of data. Thus, in many computer systems in which the DBMS operates, a form of system in which a storage device having a large-capacity disk is coupled to a computer in which the DBMS operates, and DB data is stored in the storage device is typical.
When this form of system is adopted, since data is stored on the disk of the storage device, an access to the disk occurs inevitably when performing processing (DB processing) on DBs. In particular, in very large scale DBs of petabyte class, a processing of finding certain specific data from the DB data incurs an enormous amount of time. Thus, a technique disclosed in PTL 1 is known as a technique of accelerating a retrieving processing of finding specific data among a large amount of data.
The technique disclosed in PTL 1 is a technique for multiplexing reading of data, by dynamically creating a task whenever reading data and executing the tasks in parallel. According to a DBMS which uses this technique, it is possible to improve retrieving performance dramatically as compared to a conventional DBMS that executes tasks in their occurrence order.
The DBMS divides a DB processing into processing units called tasks, executes the tasks in a highly parallel manner to submit I/Os (asynchronous I/Os) in a highly multiplexed manner to maximize storage performance to thereby improve the performance. Thus, the degree of parallelism of processing (tasks) including I/Os is very important in improving the performance. For example, the ability to submit how many I/Os to each HDD of a storage device, that is, the ability to accumulate how many tags (SCSI commands submitted from a computer to a storage device) in each HDD is important.